Abstract

Humans make prediction about physical environments and future
events through inference. Previous research has proposed that a common sense
engine implementing probabilistic programming is used to build an internal model
of the environment, and simulations of that internal model are used for
inferences. Battaglia et al.(2013) have demonstrated an application of this
formulation in physical scene understanding and stability judgment in the case of
block tower. Here we augment this formulation by including the subjects’
eye movements as a process of sampling the environment, and propose that the
underlying common sense model guides gaze toward sampling the features of the
space with relevant information for the judgments about stability. We compare a
base probabilistic model with one that takes the statistics of the saccades into
account, and argue that the additional information improves the model predictions
about subjects’ judgment.